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All Journal Teaching English as a Foreign Language Overseas Journal (TEFLO)
Raben, Serli Kalo
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Education Languange, Linguistic, Communication & Media

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A COMPARATIVE ANALYSIS OF THE ACCURACY OF MACHINE TRANSLATION IN TRANSLATING ENGLISH TO INDONESIAN Raben, Serli Kalo; Sirande, Normalia; Arrang, Judith Ratu Tandi; Ilham, Muhammad
Teaching English as a Foreign Language Overseas Journal Vol. 13 No. 1 (2025): Teaching English as a Foreign Language Overseas Journal: In Press
Publisher : Publikasi dan UKI Press UKI Toraja.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47178/t0gw3271

Abstract

Machine translation has become increasingly popular, but its accuracy is still a subject of debate. This study aims to compare the accuracy of two popular machine translation tools, Google Translate and DeepL Translate, in translating English to Indonesian. This research applied a descriptive quantitative research methodology. The research design involves comparing the accuracy of Google Translate and DeepL Translate by analyzing the output translation texts and  using narrative texts as the sample. The data collection procedure involves conducting a written test using data cards and a data sheet. The accuracy of the translations is calculated based on the percentage of accurately translated meanings. The findings of this research indicate that both Google Translate and DeepL Translate provide translations that are considered less accurate. This statement is based on the finding of accuracy occurrence  DeepL Translate outperforms Google Translate with a higher percentage. Specifically, DeepL Translate achieves an accuracy rate of 73.1%, while Google Translate lags slightly behind at 63.4%. This suggests that DeepL Translate demonstrates a better ability to produce accurate translations across the board. In conclusion, this research highlights the need for improvement in machine translation tools for translating English to Indonesian. Both Google Translate and DeepL Translate show limitations in accuracy, indicating the importance of continuing research and development in the field of machine translation.
Co-Authors Judith Ratu Tandi Arrang Muhammad Ilham Sirande, Normalia